Perturbed Adaptive Belief Propagation Decoding for High-Density Parity-Check Codes
نویسندگان
چکیده
Algebraic codes such as BCH code are receiving renewed interest their short block lengths and low/no error floors make them attractive for ultra-reliable low-latency communications (URLLC) in 5G wireless networks. This article aims at enhancing the traditional adaptive belief propagation (ABP) decoding, which is a soft-in-soft-out (SISO) decoding high-density parity-check (HDPC) algebraic codes, Reed-Solomon (RS) Bose-Chaudhuri-Hocquenghem (BCH) product codes. The key idea of ABP to sparsify certain columns matrix corresponding least reliable bits with small log-likelihood-ratio (LLR) values. sparsification strategy may not be optimal when some have large LLR magnitudes but wrong signs. Motivated by this observation, we propose Perturbed (P-ABP) incorporate number unstable LLRs into operation matrix. In addition, apply partial layered scheduling or hybrid dynamic further enhance performance P-ABP. Simulation results show that our proposed algorithms lead improved correction performances faster convergence rates than prior-art variants.
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ژورنال
عنوان ژورنال: IEEE Transactions on Communications
سال: 2021
ISSN: ['1558-0857', '0090-6778']
DOI: https://doi.org/10.1109/tcomm.2020.3047085